There is an increasing need, particularly in the fields of medicine and agriculture, to identify and characterize the molecules which participate in a wide variety of biological processes and to find new molecules capable of modulating these processes. One way to search for novel bioactive compounds is to screen libraries of natural materials or synthesized molecules, using assay techniques which can range in complexity from simple binding reactions to elaborate physiological preparations. Unfortunately, selecting molecules of interest from large ensembles or repertoires can be time-consuming and costly, and often only provides leads which require further investigation and development.
Recently, there have been several developments both in the generation of libraries and in the methods of their selection which have improved the efficiency and effectiveness of this approach. Phage display technology, largely developed in the 1990s, is an in vitro selection technique in which a protein (or peptide) is displayed on the surface of a phage virion, while the DNA encoding the protein is contained within the virion. This direct physical linkage between the displayed protein and the DNA encoding it allows for successive rounds of selection and amplification. Large phage display libraries (“PDLs”) can be generated and screened against target molecules. These PDLs may encompass an enormous number of different peptides which represent potential ligands to a variety of macromolecules such as receptors, polypeptides, enzymes, carbohydrates, and antibodies. Individual phage can be captured from the libraries by virtue of the interaction of the displayed protein with a cognate ligand, and the captured phage can be amplified by infection of bacteria. Thus, phage display technology is a very powerful tool for the selection of peptides that bind to target molecules. These peptides may find numerous applications, for example, as antigens in vaccine compositions, as enzyme inhibitors, or as agonists or antagonists of receptors.
One strategy for developing diagnostic tests and drugs for treating a disease involves the identification of key cellular components, such as proteins, that are causally related to the disease process. This can often be accomplished by looking at differences in protein composition or protein action between diseased and healthy individuals or between treated and untreated patients. Unfortunately, present methods of analyzing biomolecules are time-consuming and expensive, and suffer from inefficiencies in detection, imaging, purification, and analysis. Thus, there is a need for methods of detecting specific differences and changes between biological samples. Such methods would facilitate the identification of biological targets for diagnostic and drug development.
Although the genomics approach has advanced our understanding of the genetic basis of biological processes, it has significant limitations. For instance, the functions of products encoded by identified genes—and especially by partial cDNA sequences—are frequently unknown, and information about post-translational modifications of a protein can rarely be deduced from a knowledge of its gene sequence. It is now apparent that a large proportion of proteins undergo post-translational modifications (such as glycosylation and phosphorylation) that can profoundly influence their biochemical properties. Furthermore, protein expression is often subject to post-translational control, so that the cellular level of an mRNA does not necessarily correlate with the expression level of its gene product.
For these reasons, there is a need to supplement genomic data by studying the patterns of protein and carbohydrate expression, and of post-translational modification generally, in a biological or disease process through direct analysis of proteins, oligosaccharides, and other biomolecules. The burgeoning field of proteomics seeks to study variations in cellular protein levels between normal and diseased states by detecting and quantitating expression at the protein level, rather than the mRNA level. However, the proteomics approach faces numerous obstacles, including sample complexity, large relative abundance range, and quantitation of proteins. Technical constraints have heretofore impeded the rapid, cost-effective, reproducible, and systematic analysis of proteins and other biomolecules present in biological samples.